Economic Interrelationships and Impacts of the Aviation/Aerospace Industry in the State of Florida using Input-Output Analysis

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1 Dissertations and Theses Economic Interrelationships and Impacts of the Aviation/Aerospace Industry in the State of Florida using Input-Output Analysis Kelly Whealan George Embry-Riddle Aeronautical University - Worldwide Follow this and additional works at: Part of the Aerospace Engineering Commons, Aviation Commons, Growth and Development Commons, Income Distribution Commons, Labor Economics Commons, and the Regional Economics Commons Scholarly Commons Citation George, Kelly Whealan, "Economic Interrelationships and Impacts of the Aviation/Aerospace Industry in the State of Florida using Input-Output Analysis" (2015). Dissertations and Theses. Paper 51. This Dissertation - Open Access is brought to you for free and open access by ERAU Scholarly Commons. It has been accepted for inclusion in Dissertations and Theses by an authorized administrator of ERAU Scholarly Commons. For more information, please contact commons@erau.edu.

2 ECONOMIC INTERRELATIONSHIPS AND IMPACTS OF THE AVIATION/AEROSPACE INDUSTRY IN THE STATE OF FLORIDA USING INPUT-OUTPUT ANALYSIS by Kelly Whealan George A Dissertation Submitted to the College of Aviation in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in Aviation Embry-Riddle Aeronautical University Daytona Beach, Florida February 2015

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6 ABSTRACT Researcher: Title: Kelly Whealan George ECONOMIC INTERRELATIONSHIPS AND IMPACTS OF THE AVIATION/ AEROSPACE INDUSTRY IN THE STATE OF FLORIDA USING INPUT-OUTPUT ANALYSIS Institution: Degree: Embry-Riddle Aeronautical University Doctor of Philosophy in Aviation Year: 2015 The study provided a detailed description of the interrelatedness of the aviation and aerospace industry with principal industries in Florida and Volusia County (VC) using Input-Output (IO) analysis. Additionally, this research provided an economic impact analysis of the creation of a university research park in Daytona Beach (DB). The economic impact measures included not only direct economic output and industry employment descriptions but also described the multiplier effects in the form of indirect and induced impacts using data for This research concluded the average labor income of the aviation and aerospace industry was higher than average labor income in Florida and VC. A substantive difference between the Florida and VC average labor income for the aviation and aerospace industry existed because VC s aerospace sector was only concentrated in the search, detection, and navigation instruments manufacturing sector. VC s transport by air sector was one-fifth the size of Florida s. Differences in the aviation and aerospace industry composition between Florida and VC are important because the economic impacts from a shock to the entire aviation and aerospace industry will be distributed differently. iii

7 Since the aviation and aerospace average labor income is higher than the average labor income in Florida and VC, it would be a positive move for Florida s economy to attract and grow the aviation and aerospace industry. It would be highly unlikely that the entirety of newly created jobs would be resourced from the local population. Nonetheless, growing the aviation and aerospace industry jobs would have a positive influence on the region s economy and tax revenues. It would be a desirable course of action to spur the growth of this sector, as its direct effect would culminate with additional jobs in Florida that would bring higher wage jobs to the state. The interdependencies of the aviation and aerospace industry in Florida and VC with other industries had a positive indirect and induced effect in the economy providing almost a two-fold indirect and induced effect. However, the benefits were not equal. Florida s average labor income of the most sensitive non-aviation and aerospace industry was 15% lower than the average Florida labor income. The average labor income in VC of the most sensitive non-aviation and aerospace industry was significantly higher than the average VC labor income. Industry interdependencies also presented risk. If the aviation and aerospace industry experiences a contraction, then through the interdependencies of the industries, the region would contract twice as much as the aviation and aerospace industry. The overall impact of a university research park would benefit Florida s economy. Since the research park project is currently funded partially by public state money, 14 sectors of the economy experienced negative impacts. While the net result was an increase in additional labor income, the employment growth was characterized by gaining more lower-paying jobs while losing less higher-paying jobs. The most expected iv

8 outcome, an expansion of the aviation and aerospace industry, was not evidenced by the model results. v

9 DEDICATION I dedicate most everything I do, but more specifically, the last five years to Brent, Emmett, Kiernan, and Brennan. You are my North, South, East, and West. Whenever I am lost, all I need to do is to connect with you to navigate back to where I belong. Thank you for your patience to see me through. I told you I d come back from mostly dead for you. No more rhymes now, I mean it! Anybody want a peanut? I want to also include Emmett and Dorothy Whealan in my dedication. There is no way a few sentences can express the gratitude for everything you gave and continue to give to me. My task was to take what I inherited and earn it again to truly keep it. Between beauty won t boil the pot and being too smart is weird, it is now mine. vi

10 ACKNOWLEDGEMENTS I do have to thank my entire family, extended family, and circle of friends for staying with me during this five year journey. Especially, my Karma warriors as you always lifted me up when I was dragging. Drinks are on me. I am grateful to the members of my committee. I appreciate Dr. Tim Brady for taking on my dissertation and guidance. I may make an economist out of your after all! I am especially thankful to Dr. Ian McAndrew for his humor, support, and advice that kept me focused on the end result. Dr. Irwin Price, for his technical advice and original comments that encouraged me to pursue my topic. And finally, more thanks than I can mention, long-time colleague, Dr. Robert Clair. Working with you easily shifts between productive and humorous which always makes our projects a pleasure. I ll never be able to pay your hourly rate. Dr. Harvey Rosenblum, one of my greatest professors, sparked my interest in studying economics. There are countless faculty and staff at Embry-Riddle Aeronautical University that paved the way for this accomplishment. First and foremost, Dr. John Johnson, Dr. John Watret and Marty Smith, for providing me this opportunity. Dr. James Schultz, Dr. Tom Sieland, and Dr. Robert Materna my work dads - have provided invaluable mentoring, many times having to muster extreme patience over the years. Dr. Mike Hickey, Rodney Cruise, and Lou Seno provided interesting perspectives and discussions during my research. Dr. Dick Roach for a great laugh when I needed a break. Kathy Markwith, Susie Bencsik, and Andrea Hooper - the women that would slice through any administrative red tape that I managed to tangle myself into. And finally, everyone else at this institution that strives to constantly improve for the benefit of the vii

11 students. I am grateful to have experienced the consumer perspective of this institution and look forward to returning to the producer side! viii

12 TABLE OF CONTENTS Page Committee Signature Page... ii Abstract... iii Dedication... vi Acknowledgements... vii List of Tables... xii List of Figures... xiv Chapter I Introduction...1 Significance of the Study...4 Statement of the Problem...5 Purpose Statement...6 Research Questions...6 Delimitations...7 Limitations and Assumptions...9 Definition of Terms...10 List of Acronyms...12 Chapter II Review of the Relevant Literature...14 Industry Definitions...14 Industry Interrelatedness Studies...16 Input-Output Analysis...19 Economic Impact Studies...26 ix

13 Other Economic Impact Analysis Models...27 University Research Parks...32 ERAU s Aerospace Technology and Research Park...35 Summary...36 Chapter III Methodology...38 Research Approach...39 Study Area...40 Industry Composition and Interrelatedness...41 Economic Impact...43 Instrument Reliability...44 Instrument Validity...45 Assumptions of the Model and Limitations...46 Implications for Output...47 Summary...48 Chapter IV Results...49 Industry Sector Definitions...50 Research Question One...53 Research Question Two...57 Research Question Three...72 Results Summary...76 Chapter V Discussion, Conclusions, and Recommendations. 79 Discussion...80 Research Question One...80 x

14 Florida...80 Volusia County...80 Research Question Two...81 Research Question Three Assumptions and Limitations of Results...87 Recommendations...88 Research Park Recommendations...90 Recommendations for Future Research...90 References...93 Appendices A North American Industry Classification Code (NAICS) B University Research Park Impact to Employment by Industry and Effect in Florida, C University Research Park Impact to Labor Income by Industry and Effect in Florida, D University Research Park Impact to Value Added by Industry and Effect in Florida, xi

15 LIST OF TABLES Page Table 1 Aviation industries defined by NAICS code Aerospace industries defined by NAICS code Educational service industries defined by NAICS code An example of an Input-Output matrix for a two-sector economy Aviation industries defined by NAICS and Implan codes Aerospace industries defined by NAICS and Implan codes Composition of the aviation and aerospace industry in Florida Composition of the aviation and aerospace industry in Volusia Country, Change in Final Demand in the Aviation and Aerospace Industry in Florida, Total Impact Summary to a Change in final Demand in the Aviation and Aerospace industry in Florida, Top Ten Most Sensitive Non-Aviation and Non-Aerospace Industries by Value Added to a Change in Final Demand in the Aviation and Aerospace Industry in Florida, Top Ten Most Sensitive Non-Aviation and Non-Aerospace Industries by Employment to a Change in Final Demand in the Aviation and Aerospace Industry in Florida, xii

16 13 Top Ten Most Sensitive Non-Aviation and Non-Aerospace Industries by Labor Income to a Change in Final Demand in the Aviation and Aerospace Industry in Florida, Aviation and Aerospace Industry Sector s Multipliers in Florida, Change in Final Demand in the Aviation and Aerospace Industry in VC, Total Impact Summary to a Change in Final Demand in the Aviation and Aerospace Industry in VC, Top Ten Most Sensitive Non-Aviation and Non-Aerospace Industries by Value Added to a Change in Final Demand in the Aviation and Aerospace Industry in VC, Top Ten Most Sensitive Non-Aviation and Non-Aerospace Industries by Employment to a Change in Final Demand in the Aviation and Aerospace Industry in VC, Top Ten Most Sensitive Non-Aviation and Non-Aerospace Industries by Labor Income to a Change in Final Demand in the Aviation and Aerospace Industry in VC, Aviation and Aerospace Industry Sector s Multipliers in VC, Total Impact Summary in Florida, Tax Impacts by Category in Florida, Most Sensitive Non-Aviation and Aerospace Industries Ranked by Average Labor Income in FL, Most Sensitive Non-Aviation and Non-Aerospace Industries Ranked by Average Labor Income in VC, xiii

17 LIST OF FIGURES Page Figure 1 The Research Park Concept Total Employment Impact Summary to a Change in Final Demand in the Aviation and Aerospace Industry in Florida, Total Labor Income Impact Summary to a Change in Final Demand in the Aviation and Aerospace Industry in Florida, Total Value Added Impact Summary to a Change in Final Demand in the Aviation and Aerospace Industry in Florida, Total Intermediate Expenditures Impact Summary to a Change in Final Demand in the Aviation and Aerospace Industry in Florida, Total Employment Impact Summary to a Change in Final Demand in the Aviation and Aerospace Industry in VC, Total Labor Income Impact Summary to a Change in Final Demand in the Aviation and Aerospace Industry in VC, Total Value Added Impact Summary to a Change in Final Demand in the Aviation and Aerospace Industry in VC, Total Intermediate Expenditures Impact Summary to a Change in Final Demand in the Aviation and Aerospace Industry in VC, Total Employment Impact Summary in Florida, Total Labor Income Impact Summary in Florida, Total Value Added Impact Summary in Florida, xiv

18 1 CHAPTER I INTRODUCTION The aviation and aerospace industry have always had a significant economic impact in the areas where they have been introduced. It has been argued these are both positive and negative impacts on individual standpoints (Enterprise Florida, 2013; Florida Space Day, 2013; Harrington, J., Lee, H., Tischner, C., Duch, D., March 2012; Whealan George, 2013). Any local expansion of these industries will naturally polarize views, and there are numerous examples where resistance has delayed and even stopped expansion (Arcieri, 2014; Dale, 2014; Hilkevitch, 2013). Justification for any economic influences is often one of those aspects of the industries expansion that undergoes scrutiny at regional and national levels. Economic impact analysis can be used to mitigate this polarization if it can be demonstrated to show unbiased and real data for the economic impact. Input-Output (IO) analysis is an economic impact quantitative technique to assess how changes in a specified economy compound financially through local and regional economies (Blin & Murphy, 1973; Chiou-Shauang & Ames, 1965; Khandker, Koolwal, & Samad, 2010; Lang, 1983; Lynch, 2000). IO analysis is a widely accepted feasible method of economic impact analysis used to objectively quantify the total economic impact of an industry(s). Furthermore, IO analysis is an economic tool that can be used to review the interrelatedness with all other industries in a specified economy. This is not to say it can be a panacea for all analysis; rather, it can be applied with specific constraints to produce meaningful results that are robust. This dissertation employed IO analysis that uses a matrix of a set of linear equations for all industries in the economy to depict intra-industry relationships within an

19 2 economy. Each row in the matrix was essentially an equation representing the output from one industry broken down into inputs to other industries production or a final demand output value. The specified region studied was the State of Florida and Volusia County (VC) because of the geographic location of a proposed aviation and aerospace research park in Daytona Beach (DB) and its proximity to the desired expansion of the aviation and aerospace industry cluster within Florida and VC (Enterprise Florida, 2013). By reviewing a change in the final demand in specific industries related to a project, the resulting IO analysis output described the total induced changes in all the other industries from the initial economic event (Miller, R.E. & Blair, P.D., 2009). This research used the current, appropriate, and specific research and industry interrelatedness output accounts of economic activity. The published economic contributions to the regional economy of the aviation and aerospace industry in Florida, as well as the creation of an aerospace research park in VC were incomplete and varied. Enterprise Florida (2013) stated that Florida employs over 87,000 aerospace and aviation workers across the state. Florida Space Day (2013) published that the total number of aerospace industry employees reported in Florida was in excess of 132,000 with combined total revenue of over 17 billion U.S. dollars. To foster an expansion of the aviation and aerospace industry in Florida, the Florida Legislature s approval for $9M to build a wind tunnel at Embry-Riddle Aeronautical University (ERAU) was forecasted to spur the creation of additional engineering jobs (Embry-Riddle poised for success with research park,. 2013). The establishment of a university research park is viewed as a successful way to advance innovation and create economic growth (Battelle Technology Partnership Practice, 2013). Research parks are

20 3 emerging as strong sources of entrepreneurship, talent, and economic competitiveness for regions, states, and nations (Battelle Technology Partnership Practice, 2007). For example, ERAU partnering with an internationally renowned aircraft manufacturer is hoped to provide job opportunities and an economic boost for VC as well as the state of Florida (Embry-Riddle poised for success with research park, 2013). There are numerous industry participants, associations, educational institutions, economic development organizations, and government entities that advocate the growth of a geographic cluster of industry dedicated to the aviation and aerospace industry within Florida and VC, inter alia (Association of University Research Parks, 2013b; Enterprise Florida, 2013; Florida Space Day, 2013; Harrington, J., Lee, H., Tischner, C., Duch, D., 2012; Pisano & Shih, 2009). The objective of any research park is the promise to provide the state, the park developer, and the surrounding region, with potential economic opportunities, an improved competitive climate, and growth of high-wage employment. Florida ranks in the top five states for aerospace industry employment and contributes a large amount of economic productive output to the Florida economy (Space Florida, 2014; The Commission on the Future of the U.S. Aerospace Industry, 2002). Florida also has significant aviation and aerospace infrastructure already in place as well as the related labor force and educational institutions to support this economic development effort (Enterprise Florida, 2013; Florida Space Day, 2013; Space Florida, 2014). This dissertation provided a comprehensive description of the interrelatedness of the aviation and aerospace industry with all other industries in Florida and VC. In addition, this research offered an economic impact analysis of the creation of a university

21 4 research park in Daytona Beach (DB) that supports the expansion of an aviation and aerospace clustered industry within Florida. The measures of the economic impact included not only direct economic output and industry employment descriptions, but also described the multiplier effects from the addition of such a facility to the economy. As additional economic activity in one industry is not limited within that industry, the analysis described the additional economic activities in non-aviation and non-aerospace industry as a result of the economic impact. Significance of the Study Investment, whether public or private, attracts competing interests and will require anticipating what will be the economic importance of this project or activity. The results from this dissertation comprehensively described the additional production impact from the aviation and aerospace industry importance on all the other non-aviation and non-aerospace industries within Florida and VC with respect to production and employment. The results also highlighted any economic impacts, positive or negative, from the creation of a university research park in DB. This analysis was structured to yield information about direct, indirect, and induced effects in the form of employment figures, labor income, and total economic output for specific industries in the region. Results can be used for economic comparisons, planning, resource allocation, and identification of industry clusters.

22 5 Statement of the Problem A typical objective of regional economic policy is to diversify the economy and promote growth of beneficial industries, inter alia (Nobel Media, 2013). Potential economic policy options are often constrained by budgets requiring resources to be allocated in order to maximize their impact with respect to the desired economic result (Los, 2011). For example, the FAA evaluated and decided its investment in NextGen capabilities will result in increased air space capacity, safety enhancements, and lower fuel costs that will translate into better economic results and growth in the U.S. aviation industry. The promotion of the aerospace and aviation industries in Florida and VC have not been addressed in detail using current industry output data. The present situation has arisen from a desired expansion of the aviation and aerospace industry cluster within Florida and VC by industry and other related organizations. In addition, an economic impact analysis regarding the proposed creation of a university research park in DB has not been undertaken. Many of the existing studies are only partial analysis, do not include the multiplier affects, or are using data models that do not reflect the current economic relationships between industries (Association of University Research Parks, 2013b; Battelle Technology Partnership Practice, 2007; Embry-Riddle Aeronautical University, 2013b; Florida Space Day, 2013; Harrington, J., Lee, H., Tischner, C., Duch, D., 2012). The multiplier effects are critical as they encompass the industry interrelatedness within a specified economy. An economic analysis of Florida and VC that is based on a matrix of industry relationships identifying the aviation and aerospace industry s significance in the Florida economy was undertaken. Additionally, the

23 6 analysis can be used for decision making for future investments in regional economic growth based on a high significance of confidence. Purpose Statement The purpose of this quantitative descriptive study was to develop current, comprehensive estimates of the magnitude and importance of the aviation and aerospace industry to all other Florida industries. It presented a measure that can be used in policy analysis and in preparing other economic descriptive statistics. Additionally, the study provided an analysis of the impact of the creation of a university research park to the local economy. Given a principal objective to develop an aviation and aerospace industry s cluster in the state of Florida and VC, this study provided policy decision makers valid metrics as to the value of the industry and effects of changes on other industries with the region. Research Questions This dissertation answered descriptive research questions. RQ 1: What is the composition of the aviation and aerospace industry in the Florida and VC economy in terms of employment and economic output? RQ2: What are the interdependencies of the aviation and aerospace industry s economic relationships with other industries in Florida and VC? RQ3: What would be the impacts on the regional economy of Florida and VC if a university research park was created in DB, Florida?

24 7 Delimitations While the analysis of the results the research questions was comprehensive and can be applied to other economic events within the region, there are limitations to generalizing the specific conclusions to a region other than Florida and VC or to other industries interrelatedness measures. The relationships between the industries as represented in the IO analysis were unique to the region under study. It would be inappropriate to suggest that the interrelatedness of the aviation and aerospace industry in Florida is the same in other economic regions. An industry s multiplier effect may be different based on its geographic region and size of region. Multiplier effects may also vary widely based on the type of industry within the region and other unique factors. If one industry procures more of its production within the region relative to another industry, that industry s multiplier will be larger than the others and will have a greater impact within the region s economy. A larger region under study will typically have fewer outflows from its economy into different regions, in part due to the larger region satisfying the additional spending from any one industry (Implan Group, 2004; Miller, 2011). Typical sources of outflows or leakages from a geographical economy are purchases from outside the region, tax payments, and the region s household savings characteristics. All these examples of leakage represent money that does not keep flowing through the region s economy and thus dampens multiplier effects (Implan Group, 2004; Miller, 2011). A clustered industry whereby businesses are in the same proximity to their suppliers, service providers, or associated institutions will have a higher multiplier effect within a region than an industry that transacts from many different regions. A good example of a

25 8 clustered industry is the computer technology industry located in Silicon Valley, California. Entrepreneurs, venture capitalists, technology service companies, engineers, and programmers are located around a geographic area and Stanford s Research Park and thus became a major industrial force in the region. Other examples of geographic clusters in the US are: the Research Triangle in North Carolina, the financial industry in Connecticut, the film industry in California, and the tourism industry in both central and south Florida (Porter, 2000). Industry clusters are not limited to the US as there are other examples such as ship building in Korea, Formula 1 in England, and the auto industry in Japan. The IO data was specific to Florida and VC in terms of the economic interrelationships between industries that are present. Due to the unique characteristics of Florida, economic interrelationships with the aviation and aerospace industry may be different in another state or region. Items of significance to the aviation and aerospace industry in Florida and VC that are unique to the region are: their geographic proximity to other industries and related industry organizations, the Florida tax structure, the transportation infrastructure, and the concentration of industry-related laborers and academia. Significant structural changes in the economy would decrease the validity of the estimation of the economic impacts as time progresses past the most current data represented in the IO model. The use of IO for forecasting economic behavior is dependent upon the stability of the economy reflected in the analysis. Use of IO for forecasting in a rapidly changing economic environment or over a long-term time horizon

26 9 requires additional conditions of forecasts of future technology and detailed final demand components (Dietzenbacher et al., 2013; Leontief, 1987). Limitations and Assumptions The estimates of this research were based on the assumption that the relationships defined in the current data are maintained or constant (Day, 2013). The research park spending estimates were derived from university projections for the research park. Changes to the types of industries in a region typically change slowly and seldom have an immediate impact. There have been exceptions; however, the structural changes expected in this research are expected to be minimal. If unanticipated changes occur, the research will need to be revised accordingly with updated data. However, the principles of this methodology were robust for expected natural variations. In order to have the maximum confidence of reflective outcomes, this research will be most representative for one year or until significant structural changes in the economy take place. Examples of significant changes that can quickly restructure part of the economy are energy price or availability shocks, environmental factors, and policy redirections. Impact estimates based on a broader economic region are better than a narrowlydefined region because of the leaks in the system. An impact study can only track transactions as they are conducted within the region under study. If an area economically grows significantly or becomes more globalized, more leaks in the system occur as money moves out of the region under study and cannot be traced. Additionally, if an industry purchases most of its inputs from out of the region, the economic impact from an event is dampened.

27 10 Definitions of Terms Aviation Industry The aviation industry includes the air transportation sector providing air transportation of passengers and/or cargo using aircraft, such as airplanes and helicopters and aviation manufacturing industry comprising establishments primarily engaged in one or more of the following: (1) manufacturing or assembling complete aircraft; (2) developing and making aircraft prototypes; (3) aircraft conversion (i.e., major modifications to systems); and (4) complete aircraft overhaul and rebuilding (i.e., periodic restoration of aircraft to original design specifications) (U.S. Census Bureau, 2012). Aerospace Industry The aerospace industry includes guided missile and space vehicle manufacturing, guided missile and space vehicle propulsion unit and propulsion unit parts manufacturing, other guided missile and space vehicle parts and auxiliary equipment manufacturing (U.S. Census Bureau, 2012). Input-Output Analysis An analytical framework developed by Wassily Leontief for the study of the interdependence of industries in an economy as well as incorporating additional details of economic activity (Miller, R.E. & Blair, P.D., 2009). Direct Effect Direct effects are the economic activities resulting from business activity (Miller, R.E. & Blair, P.D., 2009)

28 11 Indirect Effect Indirect effects are those caused by inter-industry changes in business (Miller, R.E. & Blair, P.D., 2009). Induced Effect Induced effects are those impacts created by the household sector spending of those employed by the direct and indirect altered industries (Miller, R.E. & Blair, P.D., 2009). Intermediate Expenditures Intermediate expenditures are the money values spent purchasing goods and services to create an industry s production (Day, 2013). Shannon-Weaver Diversity Index The Shannon-Weaver diversity index measures economic diversity on the basis of the number of industries in a region and the distribution of employment across the industries. Smaller values of the index suggest lower diverse economies. A value of zero indicates minimum diversity with economic activity concentrated in only one industry. A value of one indicates perfect diversity with economic activity equally and broadly distributed across all industries. The most diverse economy is one in which all industries exist and have an equal share of economic activity. If a region has 100 industries and each of those industry sectors had 10 employees, then the index would be the maximum of 1.0. (Day, 2013).

29 12 List of Acronyms AAI ATRP AURP B BEA CBA DAB DB ERAU FL GDP GRP IO K M NAICS NANAI OMB RP SIC STEM Aviation and aerospace industry Aerospace Technology and Research Park Association of University Research Parks Billion Bureau of Economic Analysis Cost Benefit Analysis Daytona Beach International Airport Daytona Beach Embry-Riddle Aeronautical University Florida Gross Domestic Product Gross Regional Product Input-Output analysis Thousand Million National Accounting Industry Classification System Non-aviation and Non-aerospace Industries Office of Management and Budget Research Park Standard Industry Code Science, Technology, Engineering, and Math

30 13 S-W US VC Shannon-Weaver Diversity Index United States Volusia County

31 14 CHAPTER II REVIEW OF THE RELEVANT LITERATURE Critical to understanding a region s economy is the knowledge of how industries interact and thus how their economic events impact other industries. Reviewed literature includes the definition of industry sectors, alternatives to quantifying industry interrelationships and economic impacts, and university research park s impacts on a region s economy. Once a detailed description of the industry relationships is established, conducting what if scenarios can estimate the effects of specific significant economic events on a specified economy. With research parks emerging as an engine for growth in a region, the creation of a research park specifically dedicated to aviation and aerospace in Florida can be viewed as an economic event. A research park is a substantial investment in which sponsors strive to bring together related private organizations, academia, and government resources to collaborate on developing and commercializing new technology (Anttiroiko, 2004; Clark, 2003a; Clark, 2003b; Leyden, Link, & Siegel, 2008). Fostering a research park not only creates new technology for the industry but it also creates additional long term economic activity in a region (App, 2006; Miller, 2011). Industry Definitions Productive activity, cataloged into various classes or sectors by industrial classifications, quantifies economic activity in an economy. Industry sectors are also the means or the paths through which impacts from an economic event may be traced. Industry classifications commonly divide economic activity according to similar functions. The most detailed regional IO matrix used in this research depicts economic

32 15 activity categorized into 440 industry sector codes that relate to the North American Industry Classification Strategy (NAICS) developed under guidance by the U.S. Office and Management and Budget (OMB) (Appendix A). The NAICS is the standard for use by Federal agencies in classifying business activities into industries within the U.S. economy. By organizing through the NAICS standard, economic data is uniform and can be used in economic analysis and presentation. Business activity is assigned a NAICS code based on its primary business activity. A primary business activity is determined by the relative share of production valued by either revenue or value of shipments (U.S. Census Bureau, 2012). Tables 1, 2, and 3 define the related NAICS categories for aviation, aerospace, and education industries. Table 1. Aviation industries defined by NAICS code (U.S. Census Bureau, 2012). NAICS code Title Aircraft manufacturing Aircraft engine and engine parts manufacturing Other aircraft parts and auxiliary equipment manufacturing Scheduled passenger air transportation Scheduled freight air transportation Nonscheduled chartered passenger air transportation Nonscheduled chartered freight air transportation Other nonscheduled air transportation Petroleum refineries (aviation fuel) Other airport operations Flight training All other amusement and recreation industries Other social advocacy organizations Regulation and administration of transportation programs

33 16 Table 2. Aerospace industries defined by NAICS code (U.S. Census Bureau, 2012). NAICS code Title Guided missile and space vehicle manufacturing Guided missile and space vehicle propulsion unit and propulsion unit parts manufacturing Other guided missile and space vehicle parts and auxiliary equipment manufacturing Search, detection, navigation, guidance, aeronautical and nautical system and instrument manufacturing Other measuring and controlling device manufacturing Carbon and graphite product manufacturing Table 3. Educational service industries defined by NAICS code (U.S. Census Bureau, 2012). NAICS code Title Colleges, Universities and Professional Schools Flight training Industry Interrelatedness Studies To study industry interrelatedness and get a sense of the impact or interdependence of one industry on all the others, economists turn to economic interrelatedness studies based on general equilibrium theory (Blaug, 1986). Leon Walras is considered by many as the father of general equilibrium theory (Sandmo, 2011). In Elements of Pure Economics (1884), Walras theorized that a system of simultaneous equations as a representation of the economy could represent all markets in the economy at equilibrium (Walras, 1877). General equilibrium systems are successful because they account for the interdependence of all economic agents in the model. Blin and Murphy (1973) categorized the IO system as a very special and rich class of general equilibrium

34 17 models (Blin & Murphy, 1973). The IO matrix of a region s economy operates as a general equilibrium model and a source for the economic interpretation of the industries interrelatedness. The industry interrelatedness function becomes a useful measure in economic contexts and in the application of impact studies (Blin & Murphy, 1973; Chiou-Shauang & Ames, 1965). More complex industry relationships can be modeled using econometric models. Hunt (1996) and Hunt (1997) evaluated rival regional econometric models but found there was little consistency across the results. The differences in conclusions, oftentimes in direct conflict with alternatives, typically were explained by detailed analysis of the models underlying structures, source data sets, and treatment of data. Additionally, with the availability and consistency of data over a long time span as required in econometric models, IO analysis is an alternative option constructing a detailed snapshot of the industry linkages in a regional economy. Harris and Cox (1988) used IO analysis at an aggregate level to study the relationship the between non-traded service sector and the traded goods sectors. Momigliano and Sinniscalo (1982) used IO analysis to link employment growth and the degree of integration of service industries within the Italian economy. They detailed real effects apart from what they termed illusion effects that may suggest structural changes in inter-industry relationships from outsourcing of production by Italian manufacturing firms to specialized business services. Empirical analyses that deal with the interaction of strategic economic groups in using IO are few, other than those providing routine summaries of aggregate direct and indirect output or employment values (Jones, 1992).

35 18 Romanelli and Khessina (2005) define industries that are significant to the economic wealth of a region as dominant industry clusters. Porter (1998) concluded that the Italian footwear and fashion industry was a dominant industry not because of the number of producers in the region, but because of the interrelationships of the fashion producers with the other leather goods producers and with manufacturers of the required machinery and components. Romanelli and Khessina (2005) and Porter (1998) view the interrelatedness of industries through resource overlap rather than an input-output configuration. Porter (2000 and 2003), studying company strategy and competitiveness delineates industry clusters using co-location patterns in a region rather than IO analysis. Saric (2012) notes that in the absence of data that indicates the extent to which industries are linked with each other, the construct of interrelatedness is used as a proxy to determine clusters. Interrelatedness is a complex concept reflected by multiple indicators (Saric, 2012). Rumelt (1974) and Montgomery (1982) classified firms by similarities of products, outputs, and technologies that closely resembled the Standard Industry Classification (SIC) codes. SIC codes were the predecessor of the NAISC. They were criticized because presenting interrelatedness just by grouping industry by classification has little explanatory power (Saric, 2012). Stimpert & Dunhaime (1997) and Pehrsson (2006) determined interrelatedness of industries by surveying large diversified firms to determine their perceptions of relatedness. Stimpert and Dunhaime (1997) and Pehrsson s (2006) work related industries by product market or resource market relationships, thus not fully capturing the information present in IO links.

36 19 Saric 1 (2012) points out that IO tables are commonly used as an initial step in determining clusters. Regional data can be limited. Outside the US, the use of IO tables for regional analysis is not readily available. Researchers, then, are restricted to qualitative methodologies such as survey methods or deduction of regional IO tables (Hewings & Jensen, 2000; Kratke, 2002). However, in this study, the regional data is available and valid thus allowing the use of IO analysis for full description of the interrelatedness of industries. Input-Output Analysis And perhaps this art alone can show the links and chains by which one business hangs upon another and the dependence which all our dealings have upon each other Charles Davenant 1699 (Davenant, 1699) IO analysis, developed by Wassily Leontief in the 1930s, was a new method of analyzing the interdependence of industries within an economy. For this work, Leontief was awarded the Nobel Prize in Economic Sciences in 1973 (Miller, R.E. & Blair, P.D., 2009; Nobel Media AB, 2014). Work as early as 1759 by Quesnay described the circular flow of goods (Quesnay, 1759). Leontief s work began in 1920 evolving from the circular flow of goods as a need to develop a quantitative method for grappling with the enormous amounts of empirical data involved in all real economic situations and general equilibrium theory (Leontief, 1966). Leontief claimed the following: Input-Output analysis is a practical extension of the classical theory of general interdependence which views the whole economy of a region, a country, and even of the entire world as a single system and sets out to describe and to interpret its 1 ibid p. 15

37 20 operation in terms of directly observable basic structural relationships (Leontief, 1987, p. 860). Leontief s 1936 article, Quantitative Input and Output Relations in the Economic System of the United States and his 1937 article Interrelation of Prices, Output, Savings and Investment are recognized as the beginning of a major branch of quantitative economics (Aroche, 2009; Rose & Miernyk, 1989). The inputs of one industry are sourced from the outputs of another industry enabling the IO matrix tables users to trace where each industry uses the product of another industry. The IO matrix also allows users to discover how a change in final demand in as little as one industry can impact each other industry s output. Economic interdependencies can be described through the industry product flow accounts and relationships. Furthermore, industry interrelationships can be determined by analyzing an economy s IO matrix (Leontief, 1949). In short, the IO model can be referred to as an impact model, enabling the researcher to trace specified changes in industry activities as a result of a change in final demand. IO transactions tables are created by rows and columns of data that produce a matrix of linear equations to facilitate the recognition of the inter-industry demand relationships. Each row or equation in the matrix generally represents one industry or sector of the economy. The equation for each row describes the total value of that industry s output as the sum of all the values of that industry s output sold as final demand; the value of the industry s output used in its own production process; and the value of the industry s output that is sold as an input to other industries. The row's equation is a summation where x is the total output from industry i, z is the intermediate

38 21 output used as inputs required from industry for that industry in all other industries 1 through n, and f is the final demand of i s output (see Equation 1). x i = z i1 +.+ z in + f i (1) Final demand columns are included in the matrix that detail which sectors of final demand the industry output terminates. These final demand sectors are the major Gross Domestic Product (GDP) accounts: personal consumption, gross private domestic investment, government purchases, and net exports (exports minus imports). An example of two-industry economy is discussed and presented later using Table 4. Within the IO matrix, the columns also represent inter-industry supply relationships. Each column of the matrix represents what inputs are required from all the other industries in the economy to produce each industry s output. The equation for each column represents the total value of an industry s required inputs as the sum of all the inputs that are needed from each industry, inputs needed from its own industry, and value added inputs to total production. The column s equation is a summation where x is the total value of inputs needed from industries 1 through n for that industry plus value-added for that industry (see Equation 2). Value added includes labor, wages and profits, depreciation of capital, and taxes (George & Taylor, 1995; Miller, R.E. & Blair, P.D., 2009). x i = z 1i + + z ni + va i (2)

39 22 National income and product accounting rules are internationally accepted as a measure of a nation s economic activity (Arnold, 2011). Using these national income and product accounting rules, the value of gross national income (va i ) less the final demand (f i ) is equal to the intermediate consumption or production (x i ). This relationship provides the core of the mathematical depiction of the interrelatedness of the industries in the economy. The matrix of simultaneous equations (Equation 3) represents the total accounting for production in the economy for one year (Miller, R.E. & Blair, P.D., 2009). In Equation 3, x and f represent the column vectors of industries one through i while Z reflects the matrix of intermediate outputs from industry one thru i to each industry. x = Z i + f (3) Table 4 is an example of an input-output matrix of a two-sector economy. The only two sectors in this economy are manufacturing and services. Each row s equation represents the total value of that industry s output as the sum of all the values of that industry s output sold as final demand, the value of the industry s output used in its own production process, and the value of the industry s output that is sold as an input to other industries. The manufacturing sector uses $10 of its own production; it sells $40 to the service sector; and sells $50 as final demand for a total output of $100. Each column s amount represents the total value of an industry s required inputs as the sum of all the inputs that are needed from each industry, inputs needed from its own industry, and value added inputs to total production. The services sector requires $30 from the manufacturing sector and $25 from its own sector as inputs as well as $85 of value-added inputs to show a total outlay of $140. Value added represents employee compensation, government services paid for by taxes, interest payments, rental payments, and profit. It

40 23 is possible to expand this economy internationally by adding a column for outputs destined for export and a row for inputs from imports (Miller, R.E. & Blair, P.D., 2009). Table 4. An example of an Input-Output matrix for a two-sector economy. Sector Manufacturing Services Final Demand Total Output Manufacturing Services Value Added Total Output A region s IO table can be used to assess industry production requirements inputs by simulating a change in one or more industries. Simulating such a change is typically represented as a change to final industry demand(s) and allows inspection on the expected impacts in all the other industries (George & Taylor, 1995). This manipulation is essentially solving a matrix algebraic problem of the number of industries or sectors by one vector representing the changed final demand(s) using numerical analysis software and noting the resulting vector representing the change in output for each industry. Changes in one industry affect other industries and are allowed to feed back on the original industry until the disequilibrium from the shock significantly dampens (Min Tam, 2008; Pereira & Polenske, 1996; Polenske, Robinson, K. Hong, Moore, & Stedman, 1992). With a full IO matrix table, the Leontief inverse (L) can be constructed (Equation 4). L = (I-A) -1 (4)

41 24 Leontief s inverse is the most influential tool in IO analysis because it captures all the indirect effects in the region s economy. The Leontief inverse is also known as the total requirements matrix (Miller, R.E. & Blair, P.D., 2009). The total requirements matrix represents the dependence of each industry s output on the values of the economy s final demand. Matrix A is an industry by industry square matrix showing the intermediate use of goods by all industries. Using an identity matrix (I), we can determine the requirements from each industry (x) to satisfy the total outputs for each industry (y) (Equation 5). Equation 5 explicitly is displayed to capture the interdependence of the region s industries as the output of each industry sector is dependent upon each industry sector s final demand and output (Miller, R.E. & Blair, P.D., 2009). x = (I-A) -1 y (5) IO analysis accommodates or accounts for three principal types of effects or impacts in the economy: direct, indirect, and induced. Direct impacts are those effects from business activity. Indirect impacts are those caused by inter-industry changes in business. Induced effects are those impacts created by the household sector spending of those employed by the direct and indirect altered industries (Miller, R.E. & Blair, P.D., 2009). Since the IO approach accounts for changes of inputs to industries based on changing outputs of industries, it is possible to achieve a more precise calculation of the impacts of a given or potential change in the economy. Input-output analysis can be thought of as documenting and exploring the precise systems of inter-industry exchange

42 25 through which different components of regional product become different components of regional income (Bendavid-Val, 1972, pp.87-88). From IO analysis, a comprehensive description of the inter-industry structure of an economy with strategic industries and opportunities for income and/or employment impacts can be analyzed (Day, 2013; Implan Group, 2004; Lynch, 2000; Miller, R.E. & Blair, P.D., 2009). The Leontief inverse is the basis of the multiplier effect referred to in IO analysis. This multiplier is the source of impact analysis that is widely accepted in policy design (Baumol & Wolff, 1994). IO analysis is accepted as a reliable method for descriptive analysis, forecasting, and assessing policy impact scenarios (Dietzenbacher & Lahr, 2008), inter alia. An IO model s usefulness is in the ability to estimate the indirect impacts of a final demand change by detailing the interdependency of the economy s industry. Isard, et al. (1989) maintain that because of IO s interdependency of industry capabilities, it is an indispensable part of economic impact research. IO models produce a multiplier index that is useful in measuring the total impact of a change in final demand on inter-industry demand that can be used for forecasting, and by extended application, employment impacts (Stimson, Stough, & Roberts, 2002). IO analysis has been used before for a wide range of economic impact studies, as well as to compile the economic impact analysis for a university research park within a region. When IO analysis is not used, survey studies, case studies, cost benefit analysis, or econometric models are employed; however, that is not a function of this research. The researchers for all seven economic impact studies published by the Association of

43 26 University Research Parks (AURP) used IO analysis as the tool for projecting the impact on the region (Association of University Research Parks, 2013b). IO analysis is not without its weaknesses. In doing an IO analysis, the researcher must assume there are no substitutions of inputs within the production process. For example, a change in final demand that would lead to a shortage of inputs in certain sectors of the economy would most likely induce higher market prices for those inputs, and some processes might try to adopt a change in the input mix of production. IO matrices are based on transactions over the period of one year, and any irregularities or short term trends can either be exacerbated or lost in the analysis (Bendavid-Val, 1972). IO models assume a linear relationship between a change in demand and a change in inputs and outputs that minimizes the impacts of externalities and changes in returns to scale. IO does not directly capture natural resource externalities that are not traded in the markets such as pollution and, does not answer the more subjective question of whether a society has qualitatively improved, or more efficient allocation of resources (Letson, 2002). Economic Impact Studies Like in an ant colony, little decisions on a micro level can have a big impact on a macro level. (Ted Talks, 2008) There is typically a need to evaluate the economic impact of major initiatives within an economy to facilitate decision making by policy makers and investors. Economic impact is defined as any type of event that results in an addition or loss of spending in an economy. An economic impact study seeks to describe the cumulative effects of any significant change or shock within an economy, to include direct, indirect,

44 27 and induced effects (Day, 2013). Examples of economic impacts are the opening or closing of a military base, building a sports stadium or convention facility, or recovery from natural disasters. For this research, the creation and operation of a university research park in Daytona Beach, Florida is the economic impact event to be analyzed. Other Economic Impact Analysis Models There are other methods of regional economic impact analysis, specifically, econometric modeling, inter alia (Isard, Azis, Drennan, Miller, Salzman, & Thorbecke, 1998a). Econometrics is the building of a mathematical model grounded in economic theory and statistically tested to determine if the model sufficiently describes the underlying phenomenon. Techniques such as time dependent, cross-sectional, and dummy variables can be included in an econometric model. Such models are used to test the validity of a theory, forecast values of dependent variables, or predict the results of a policy decision. Leontief and other followers critiqued studying economic impacts alternatively by way of econometric modeling. The main critique was of contemporary economists spending more time building sophisticated statistical models on data with possible validity issues (Pressman, 1999). Econometrics modeling creates models that either abstractly or theoretically describe relationships that Leontief argued were essentially built-in rather than discovered. Econometric models used for impact or forecasting typically take three forms: autoregressive models, reduced-form models, and large scale structural models (Lang, 1983). Model builders create assumptions and then create

45 28 models that use these assumptions. The model works if the assumptions are true (Friedman, 1953; Pressman, 1999; Samuelson, 1958). Bergmann, Kehoe, and Levine (1982) endorsed general equilibrium models over econometric models as tools for policy analysis. General equilibrium models like IO analysis do not have a time component that allows for infinite feedback loops to reach equilibrium. Econometric models often have an artificial truncation to a finite time horizon that can cause the calculated equilibrium to be rather sensitive to the truncation. They note that Samuelson (1958) even admitted that as a model s time period continues to be lengthened; it not only supplies more information but also introduces more unknowns into a model (Bergman, Jorgenson, & Zalai, 1990; Samuelson, 1958). Lucas (1976) was a strong advocate of solving problems through the application of economic tools to real-world data. He critiqued economic modeling because many assumptions embodied within models were unrealistic; however, if the model behaved statistically well, it could have been considered a good model. The Lucas critique went even further by saying that once policy was changed, the econometric model used in forecasts was invalid (Lang, 1983; Lucas, 1976). Friedman (1953) argued that a theory s validity should be based on its predictive accuracy rather than consideration of realistic assumptions. Focusing on the predictive validity of models negates or shadows understanding the underlying relationships in the economy when making policy and predictive statements. With IO analysis, the focus is not on the statistical predictive accuracy but the true state of the underlying industry interrelationships.

46 29 Econometric testing assumes economic relationships are stable over time and can shadow any weaknesses in the data (Chow, 1960; Pressman, 1999). Because economic relationships are dependent on individual interactions, it is unrealistic to assume the structure of their relationships does not change over time causing econometric models to weaken. Chow echoes Lucas s and Friedman s critique of econometric models. Rather than estimating values and theoretical models, Leontief believed that economists should investigate the empirical data and the relationships within them to then determine how to solve economic problems. IO became popular after World War II as governments began to work on comprehensive economic development projects because this tool would allow a policy maker to project the consequences of changes in economic policy. Since Leontief derived IO analysis from early Soviet economic planning methods, Hungarian economists and other countries adopted this method as a Socialist tool. IO analysis quickly became a casualty of the political environment in the US (Bockman, 2011). The U.S. Bureau of Labor Statistics (BLS) constructed a 50-sector matrix of inter-industry transactions modeled on the 1947 U.S. economy and projected the U.S. economy in 1950 (Cornfield, Evans, & Hoffenberg, 1950). Some industry leaders including, General Motors Incorporated and U.S. Steel executives viewed this approach as push button planning that subverts private enterprise (Kye's K.O's input-output studies, 1953). By 1953, public funding to U.S. departments supporting the construction of U.S. IO tables was terminated thus ending the public research initiative (The Netherlands Economic Institute, 1953). Research on IO analysis continued through U.S. universities with foundation funds and economists from approximately 40 other countries (The

47 30 Netherlands Economic Institute, 1953). In the 1970s, the economic environment moved from government planning and directed changes toward more of a market-directed form of economic development (Pressman, 1999). Interest in IO analysis waned as economists turned more to modeling (Pressman, 1999). In addition, the government resources for the data collection piece of IO tables and the computer modeling requirements for IO analysis were tremendous. It was in the 1960s that computers were used to calculate the matrices and required much more time than using today s computing power (Lal, 2000). Furthermore, the data collected and used for policy analysis would be considerably out of date when released for publication. For example, the U.S. Bureau of Economic Analysis (BEA) updates a benchmark IO table every five years and publishes a yearly higher level aggregated IO table for use. Despite the fact that IO analysis was downgraded by U.S. politics, it is still used overwhelmingly and internationally (Kye's K.O's input-output studies, 1953; Bockman, 2011). Economics Systems Research is a peer-reviewed journal of the International Input-Output Association (IIOA). Implan Incorporated, a company born from its academic roots at the United States Forest Service and University of Minnesota, compiles IO data for all states and publishes in a useful timeframe, typically between one and two years time lag. Murray and Wood (2010) present the academic and expanding social significance of IO analysis for the most reliable analytical method for enumerating economic transactions by industry sector. IO analysis proves useful for not only economic analysis but can be applied to environmental, sustainability, and social wellbeing studies (Wiedmann, 2010).

48 31 Another method of studying economic impacts is to use a simple economic base model where only basic and non-basic sectors are detailed (Dinc & Haynes, 1999; Haig, 1928; Quintero, 2007). Any economic impacts can be traced through multiplier effects, commonly referred to as ripple effects, that only analyze at the basic and non-basic sector levels, and gross changes are aggregated to those levels. Inter-industry transactions and financial flows are not included. Typically, economic base analysis assumes broad multipliers are applied to the sectors and the entire economy. Despite the usefulness of the economic base models, Galambos and Schreiber (1978) recommend IO analysis to obtain a more complete, detailed picture of the economic relationships than what is available in economic base models. Here again, the assumptions of exports as a sole source of economic growth, that one industry s exports does not affect another s, and no feedback among industries within a region weaken its conclusions (Davis, 1990). Drennan (1997) published a paper that said the assumptions embodied within the economic base model are just silly and wrong. Cost benefit analysis (CBA) is another form of economic impact analysis sometimes used when policies are evaluated. During the first month of the Reagan administration, President Reagan issued Executive Order that called for a CBA of all proposed regulations (Cowen, 1998). CBA compares the gross benefits of a policy or change with the opportunity costs of that change. If the benefits are greater than the costs, then typically the policy is considered positive or economically viable. CBA formats vary greatly as some seek to include estimates of social benefits or costs, environmental impacts, efficiency estimates, and price impacts (Mishan & Quah, 2007). As with the value of any model, the information depends on the accuracy of the

49 32 individual costs and benefit estimates. Usually the outcome of a CBA is a generation of an individual value that is used for justification or feasibility decisions rather than a description of the impacts within the economy. IO analysis deals strictly with transactions and provides more intra-industry information for a full description of impacts from any project. University Research Parks The AURP defines a university research park as a property-based venue that is specifically designed for research and commercialization, to create partnerships between universities and research organizations, to encourage new corporate growth, translate technology, and drive technology-led economic development (Association of University Research Parks, 2013b; Hong, Li, & Zho, 2014). The university research park is a vehicle that brings stakeholders in innovation together, the so-called triple helix (Jongwanich, Kohpaiboon, & Yang, 2014). Typically, a research park will capitalize on a region s unique strengths and clustering of like-industry participants. AURP reports that there are over 700 research, science, and technology parks in various stages of development and operation globally, of which 170 are in North America. Research parks constitute an important mechanism for technology transfer from a university to strategic development of a region s economy (Anttiroiko, 2004; Clark, 2003a; Clark, 2003b; Leyden et al., 2008). Research parks economic impacts include investment spending, which is a one-time impact that multiplies through the economy and then subsides, and daily operations that continue with the park s operation. University research parks provide a best practice of focusing on innovation and thus,

50 33 regional economic growth and competitiveness. This concept is depicted in Figure 1 (Battelle Technology Partnership Practice, 2013). Pisano and Shih (2009) found that firms within an industry benefit from geographic clusters or being co-located at a research park. Cumming & Sofia (2013) identified the factors affecting the success of a research park that will foster economic growth. Further, Pisano and Shih (2009) coined the phrase industrial commons for the phenomenon that occurs as an established research park cycles and feeds economic growth. Research park success breeds new investments and an influx of organizations that, in turn, spawns economic growth, and breeds additional investment. Siemiatycki (2013) presented that urban planning and policy agenda literature yielded universities research activities special power to spur regional economic growth. Literature has traced the rise of the entrepreneurial university where the university role expands past research and teaching to include explicit local economic development (Slaughter & Leslie, 1999; Srinivas & Viljamaa, 2006). This cycle is exactly what the IO analysis intends to describe (Adventus Research Inc., 2010; Lester, 2005). University research parks that have won the outstanding Research Science Park Award from AURP for recognition of bringing technology from the laboratory to viable businesses and promoting the growth of business, jobs, and public revenue include the University of Oklahoma Research Campus (2013), Buffalo Niagara Medical Campus (2012), Research Park at the University of Illinois at Urbana-Champaign (2011), and Virginia Tech Corporate Research Center (2010) (Association of University Research Parks, 2013a).

51 34 Universities, federal labs, non-profit R&D institutions Research Partners Flow of Talent Exchange of Ideas Access to labs and specialized equipment Private Companies Research Parks Communities generating innovation, technology and knowledge Growth of existing companies Creation of new companies Commercialization of Intellectual Property Generation of Jobs and Income Figure 1. The Research Park Concept (Source: Battelle Report). University research parks provide a best practice of focusing on innovation and thus, regional economic growth and competitiveness. There are some critics of the premise that university and university research parks play a strong role in regional economic growth. Mayer s (2007) study of growing hightechnology regions dismissed the necessity of a university research park. Gertler (2010) concluded that universities are a supporting rather than a causal role of economic growth. Levine (2009) noted there is not enough empirical research to conclude that academic